Voxel-based logistic analysis of PPMI control and Parkinson's disease DaTscans

Neuroimage. 2017 May 15;152:299-311. doi: 10.1016/j.neuroimage.2017.02.067. Epub 2017 Feb 27.

Abstract

A comprehensive analysis of the Parkinson's Progression Markers Initiative (PPMI) Dopamine Transporter Single Photon Emission Computed Tomography (DaTscan) images is carried out using a voxel-based logistic lasso model. The model reveals that sub-regional voxels in the caudate, the putamen, as well as in the globus pallidus are informative for classifying images into control and PD classes. Further, a new technique called logistic component analysis is developed. This technique reveals that intra-population differences in dopamine transporter concentration and imperfect normalization are significant factors influencing logistic analysis. The interactions with handedness, sex, and age are also evaluated.

Keywords: DaTscan; Logistic Lasso; Logistic Principal Components; PPMI; Parkinson's disease.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Brain / diagnostic imaging*
  • Brain Mapping / methods*
  • Caudate Nucleus / diagnostic imaging
  • Disease Progression
  • Female
  • Globus Pallidus / diagnostic imaging
  • Humans
  • Imaging, Three-Dimensional / methods*
  • Machine Learning
  • Male
  • Middle Aged
  • Parkinson Disease / classification
  • Parkinson Disease / diagnostic imaging*
  • Principal Component Analysis
  • Putamen / diagnostic imaging
  • Signal Processing, Computer-Assisted
  • Tomography, Emission-Computed, Single-Photon / methods*
  • Tropanes / administration & dosage

Substances

  • Tropanes
  • 2-carbomethoxy-8-(3-fluoropropyl)-3-(4-iodophenyl)tropane